A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization
Climate change and population growth risk the world's food supply. Annual crop yield
production is one of the most crucial components of the global food supply. Moreover, the …
production is one of the most crucial components of the global food supply. Moreover, the …
Deep learning-based estimation of crop biophysical parameters using multi-source and multi-temporal remote sensing observations
Remote sensing data are considered as one of the primary data sources for precise
agriculture. Several studies have demonstrated the excellent capability of radar and optical …
agriculture. Several studies have demonstrated the excellent capability of radar and optical …
DeepVeg: Deep learning model for segmentation of weed, canola, and canola flea beetle damage
M Das, A Bais - IEEE access, 2021 - ieeexplore.ieee.org
Farmers around the world face the challenge of growing more food for the increasing world
population. On top of that, external threats such as pests (weeds and insects) pose a threat …
population. On top of that, external threats such as pests (weeds and insects) pose a threat …
QuanCro: a novel framework for quantification of corn crops' consistency under natural field conditions
Crop population and inter-plant spacing in corn farms can provide useful insight into plant
phenotypic analysis and informed establishment decisions, improving crop productivity …
phenotypic analysis and informed establishment decisions, improving crop productivity …
LodgeNet: an automated framework for precise detection and classification of wheat lodging severity levels in precision farming
Wheat lodging is a serious problem affecting grain yield, plant health, and grain quality.
Addressing the lodging issue in wheat is a desirable task in breeding programs. Precise …
Addressing the lodging issue in wheat is a desirable task in breeding programs. Precise …
Detection and Mapping of Kochia Plants and Patches using High-Resolution Ground Imagery and Satellite Data: Application of Machine Learning
The presence of Kochia weed is harmful to crop production. It can grow well in harsh
conditions and is resistant to common herbicides like glyphosate. It causes stress to crops …
conditions and is resistant to common herbicides like glyphosate. It causes stress to crops …
Local-Global Feature Capture and Boundary Information Refinement Swin Transformer Segmentor for Remote Sensing Images
R Lin, Y Zhang, X Zhu, X Chen - IEEE Access, 2024 - ieeexplore.ieee.org
Semantic segmentation of urban remote sensing images is a highly challenging task. Due to
the complex background, occlusion overlap, and small-scale targets in urban remote …
the complex background, occlusion overlap, and small-scale targets in urban remote …
An assessment of the machine learning algorithms used in agriculture
M Tahaseen, NR Moparthi - 2021 5th International Conference …, 2021 - ieeexplore.ieee.org
Agriculture is considered as the backbone of India. Agriculture plays a vital role for meeting
the food demands of growing population. To improve the crop yield, effective measures are …
the food demands of growing population. To improve the crop yield, effective measures are …
Design of a High-Efficiency Temporal Engine for Real-Time Spatial Satellite Image Classification Using Augmented Incremental Transfer Learning for Crop Analysis
Satellite image processing is a multidomain task which involves design of image capturing,
denoising, segmentation, feature extraction, feature reduction, classification, and post …
denoising, segmentation, feature extraction, feature reduction, classification, and post …
Mapping Soil Organic Matter Under Field Conditions
Soil Organic Matter (SOM) is a key component for sustainable agriculture planning and soil
management. Nutrient analysis, spectroscopy and digital soil imaging are commonly used to …
management. Nutrient analysis, spectroscopy and digital soil imaging are commonly used to …